Synthesis and characterization of 3,4-dihydroxyphenyl acetic acid esters and study of their efficacy in bulk fish oil.

Lipophilization of natural antioxidants is a proven strategy to enhance the solubility in bulk oil systems, thereby increasing their efficacy against oxidative degradation. This study aims to synthesize esters of 3,4-dihydroxyphenylacetic acid (3,4-DHPA) using Amberlyst-15 and to study the application of these esters in refined fish oil. Lipophilic esters were synthesized by esterification and transesterification of 3,4-DHPA in various solvent systems. Esters of methanol, butanol and hexanol were obtained with percent conversion of 81.1, 69.3 and 78.8 respectively, and were subjected to molecular characterization and in vitro oxidant assays. The 3,4-DHPA and its methyl ester showed 36% reduction in the TOTOX value over 30 days of storage. The length of the acyl chain in the ester was found to exert a high influence on its efficacy and lipophilicity. This is the first report of 3,4-DHPA and its lipophilic esters studied for enhancing the oxidative stability of fish oil.

Integrative toxicogenomics: Advancing precision medicine and toxicology through artificial intelligence and OMICs technology.

More information about a person's genetic makeup, drug response, multi-omics response, and genomic response is now available leading to a gradual shift towards personalized treatment. Additionally, the promotion of non-animal testing has fueled the computational toxicogenomics as a pivotal part of the next-gen risk assessment paradigm. Artificial Intelligence (AI) has the potential to provid new ways analyzing the patient data and making predictions about treatment outcomes or toxicity. As personalized medicine and toxicogenomics involve huge data processing, AI can expedite this process by providing powerful data processing, analysis, and interpretation algorithms. AI can process and integrate a multitude of data including genome data, patient records, clinical data and identify patterns to derive predictive models anticipating clinical outcomes and assessing the risk of any personalized medicine approaches. In this article, we have studied the current trends and future perspectives in personalized medicine & toxicology, the role of toxicogenomics in connecting the two fields, and the impact of AI on personalized medicine & toxicology. In this work, we also study the key challenges and limitations in personalized medicine, toxicogenomics, and AI in order to fully realize their potential.

Probing the synergistic effects of rutin and rutin ester on the oxidative stability of sardine oil.

Multicomponent antioxidant mixture is proved to be highly effective in imparting oxidative stability to the edible oil. It is believed that the high efficacy of those mixtures is due to the synergistic effect exhibited by two or more components. The current study aims to analyse the synergistic effect of a flavonoid and its corresponding ester in improving the oxidative stability of n-3 PUFA rich sardine oil. The oxidative stability of rutin, esterified rutin and their combinations at three different concentrations was studied in sardine oil stored at 37 ºC for 12 days in contact with air under darkness. The combination of rutin and rutin ester showed maximum reduction of 54.2% in oxidation at 100 mg/kg and 150 mg/kg. Perhaps this is the first report on the synergistic effect of a flavonoid and its lipophilized ester for improving the oxidative stability of n-3 PUFA rich oil.

Micropatterned Neurovascular Interface to Mimic the Blood-Brain Barrier's Neurophysiology and Micromechanical Function: A BBB-on-CHIP Model.

A hybrid blood-brain barrier (BBB)-on-chip cell culture device is proposed in this study by integrating microcontact printing and perfusion co-culture to facilitate the study of BBB function under high biological fidelity. This is achieved by crosslinking brain extracellular matrix (ECM) proteins to the transwell membrane at the luminal surface and adapting inlet-outlet perfusion on the porous transwell wall. While investigating the anatomical hallmarks of the BBB, tight junction proteins revealed tortuous zonula occludens (ZO-1), and claudin expressions with increased interdigitation in the presence of astrocytes were recorded. Enhanced adherent junctions were also observed. This junctional phenotype reflects in-vivo-like features related to the jamming of cell borders to prevent paracellular transport. Biochemical regulation of BBB function by astrocytes was noted by the transient intracellular calcium effluxes induced into endothelial cells. Geometry-force control of astrocyte-endothelial cell interactions was studied utilizing traction force microscopy (TFM) with fluorescent beads incorporated into a micropatterned polyacrylamide gel (PAG). We observed the directionality and enhanced magnitude in the traction forces in the presence of astrocytes. In the future, we envisage studying transendothelial electrical resistance (TEER) and the effect of chemomechanical stimulations on drug/ligand permeability and transport. The BBB-on-chip model presented in this proposal should serve as an in vitro surrogate to recapitulate the complexities of the native BBB cellular milieus.

Advances in Smoking Related In Vitro Inhalation Toxicology: A Perspective Case of Challenges and Opportunities from Progresses in Lung-on-Chip Technologies.

The inhalation toxicology of multifaceted particulate matter from the environment, cigarette smoke, and e-cigarette liquid vapes is a major research topic concerning the adverse effect of these items on lung tissue. In vitro air-liquid interface (ALI) culture models hold more potential in an inhalation toxicity assessment. Apropos to e-cigarette toxicity, the multiflavor components of the vapes pose a complex experimental bottleneck. While an appropriate ALI setup has been one part of the focus to overcome this, parallel attention towards the development of an ideal exposure system has pushed the field forward. With the advent of microfluidic devices, lung-on-chip (LOC) technologies show enormous opportunities in in vitro smoke-related inhalation toxicity. In this review, we provide a framework, establish a paradigm about smoke-related inhalation toxicity testing in vitro, and give a brief overview of breathing LOC experimental design concepts. The capabilities with optimized bioengineering approaches and microfluidics and their fundamental pros and cons are presented with specific case studies. The LOC model can imitate the structural, functional, and mechanical properties of human alveolar-capillary interface and are more reliable than conventional in vitro models. Finally, we outline current perspective challenges as well as opportunities of future development to smoking lungs-on-chip technologies based on advances in soft robotics, machine learning, and bioengineering.

Emerging Application of Nanorobotics and Artificial Intelligence To Cross the BBB: Advances in Design, Controlled Maneuvering, and Targeting of the Barriers.

The blood-brain barrier (BBB) is a prime focus for clinicians to maintain the homeostatic function in health and deliver the theranostics in brain cancer and number of neurological diseases. The structural hierarchy and in situ biochemical signaling of BBB neurovascular unit have been primary targets to recapitulate into the in vitro modules. The microengineered perfusion systems and development in 3D cellular and organoid culture have given a major thrust to BBB research for neuropharmacology. In this review, we focus on revisiting the nanoparticles based bimolecular engineering to enable them to maneuver, control, target, and deliver the theranostic payloads across cellular BBB as nanorobots or nanobots. Subsequently we provide a brief outline of specific case studies addressing the payload delivery in brain tumor and neurological disorders (e.g., Alzheimer's disease, Parkinson's disease, multiple sclerosis, etc.). In addition, we also address the opportunities and challenges across the nanorobots' development and design. Finally, we address how computationally powered machine learning (ML) tools and artificial intelligence (AI) can be partnered with robotics to predict and design the next generation nanorobots to interact and deliver across the BBB without causing damage, toxicity, or malfunctions. The content of this review could be references to multidisciplinary science to clinicians, roboticists, chemists, and bioengineers involved in cutting-edge pharmaceutical design and BBB research.